“…We modeled partial observability by substituting an estimate of male abundance ( N̂ ) for the true abundance ( N ) in harvest models, mimicking a situation where male abundance estimates are used to update target harvests over time in a state‐dependent manner. We simulated abundance estimates as normal random variables, , with the mean centered on the true abundance of males ( m ) at the start of spring hunting ( s ) in year t () and a constant coefficient of variation ( Supplement 1, available online in Supporting Information) that was estimated empirically from abundance estimates generated by Gast et al (). To understand the effects of partial observability on performance of harvest policies, we also replicated all simulations without observation error, assuming 0 and therefore .…”